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Philip Russom

In most organizations today, data and other information are managed in isolated silos by independent teams using assorted data management tools for data quality, integration, governance, meta- and master data management, content management, and so on. The lack of coordination among data management disciplines leads to redundant team staffing and limited developer productivity. Even worse, data-driven business initiatives suffer (including BI, CRM, and business operations), due to low data-quality data, incomplete information, inconsistent data definitions, and non-compliant data. Besides avoiding these problems, the best reasons for coordinating master data, quality, governance, and other data management disciplines are to promote technical efficiencies and to support strategic, data-oriented business goals.